Evaluation of the maintainability of object-oriented software

Henry, Sallie M.; Humphrey, Matthew C.; Lewis, John A.

doi:10.1109/tencon.1990.152642

Cited by 12 publications

(2 citation statements)

References 7 publications

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“…Since the opinion of subjects regarding the experiment they participate in can influence their performance, we measured their opinion [21]. We administered a paper-based questionnaire after the experiment, in which we asked how difficult subjects found the tasks, how motivated they were to solve the tasks, and whether they think they would have performed differently with the other version of MobileMedia.…”

Section: B Materialsmentioning

confidence: 99%

Exploring Software Measures to Assess Program Comprehension

Feigenspan

Apel

Liebig

et al. 2011

2011 International Symposium on Empirical Software Engineering and Measurement

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Software measures are often used to assess program comprehension, although their applicability is discussed controversially. Often, their application is based on plausibility arguments, which, however, is not sufficient to decide whether software measures are good predictors for program comprehension. Our goal is to evaluate whether and how software measures and program comprehension correlate. To this end, we carefully designed an experiment. We used four different measures that are often used to judge the quality of source code: complexity, lines of code, concern attributes, and concern operations. We measured how subjects understood two comparable software systems that differ in their implementation, such that one implementation promised considerable benefits in terms of better software measures. We did not observe a difference in program comprehension of our subjects as the software measures suggested it. To explore how software measures and program comprehension could correlate, we used several variants of computing the software measures. This brought them closer to our observed result, however, not as close as to confirm a relationship between software measures and program comprehension. Having failed to establish a relationship, we present our findings as an open issue to the community and initiate a discussion on the role of software measures as comprehensibility predictors.

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Section: B Materialsmentioning

confidence: 99%

Exploring Software Measures to Assess Program Comprehension

Feigenspan

Apel

Liebig

et al. 2011

2011 International Symposium on Empirical Software Engineering and Measurement

View full text Add to dashboard Cite

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“…The immediate goal of this research is to relate structural attribute measures intended to quantify important characteristics of object-oriented software, such as size, polymorphism, inheritance, coupling, and cohesion to external quality indicators such as fault proneness, change impact, reusability, development effort and maintenance effort. Most of these studies have used static analysis of code and design documents to quantify the internal software properties [1,4,5,[7][8][9][10][11][12][13][14][15][16][17][18][21][22][23][24][25]27]. Static structural attribute measures, and in particular various measures of coupling, have been shown to be reasonably accurate indicators of external quality attributes, although the state of practice indicates that work still remains before the results can be generalized and practical (industrial) benefits can be demonstrated, cf.…”

Section: Introductionmentioning

confidence: 99%

Dynamic coupling measures for object-oriented software

Arisholm

Proceedings Eighth IEEE Symposium on Software Metrics

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The relationships between coupling and external quality factors of object-oriented software have been studied extensively for the past few years. For example, several studies have identified clear empirical relationships between class-level coupling and the fault-proneness of the classes. A common way to quantify the coupling is through static code analysis. However, the resulting static coupling measures only capture certain underlying dimensions of coupling. Other dependencies regarding the dynamic behavior of software can only be inferred from run-time information. For example, due to inheritance and polymorphism, it is not always possible to determine the actual receiver and sender classes (i.e., the objects) from static code analysis. This paper describes how several dimensions of dynamic coupling can be calculated by tracing the flow of messages between objects at run-time. As a first evaluation of the proposed dynamic coupling measures, fairly accurate prediction models of the change proneness of classes have been developed using change data from nine maintenance releases of a large SmallTalk system. Preliminary results suggest that dynamic coupling may also be useful for developing prediction models and tools supporting change impact analysis. At present, work on developing a dynamic coupling tracer and ripple-effect prediction models for Java programs is underway.

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Evaluating inheritance depth on the maintainability of object-oriented software

Daly

Brööks

Miller

et al. 1996

Empirical Software Engineering

140

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This empirical research was undertaken as part of a multi-method programme of research to investigate unsupported claims made of object-oriented technology. A series of subject-based laboratory experiments, including an internal replication, tested the effect of inheritance depth on the maintainability of object-oriented software. Subjects were timed performing identical maintenance tasks on object-oriented software with a hierarchy of three levels of inheritance depth and equivalent object-based software with no inheritance. This was then replicated with more experienced subjects. In a second experiment of similar design, subjects were timed performing identical maintenance tasks on object-oriented software with a hierarchy of five levels of inheritance depth and the equivalent object-based software. The collected data showed that subjects maintaining object-oriented software with three levels of inheritance depth performed the maintenance tasks significantly quicker than those maintaining equivalent object-based software with no inheritance. In contrast, subjects maintaining the object-oriented software with five levels of inheritance depth took longer, on average, than the subjects maintaining the equivalent object-based software (although statistical significance was not obtained). Subjects' source code solutions and debriefing questionnaires provided some evidence suggesting subjects began to experience difficulties with the deeper inheritance hierarchy. It is not at all obvious that object-oriented software is going to be more maintainable in the long run. These findings are sufficiently important that attempts to verify the results should be made by independent researchers

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Evaluation of the maintainability of object-oriented software

Cited by 12 publications

References 7 publications

Exploring Software Measures to Assess Program Comprehension

Exploring Software Measures to Assess Program Comprehension

Dynamic coupling measures for object-oriented software

Evaluating inheritance depth on the maintainability of object-oriented software

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